Optimization of Coconut (Cocos nucifera) Milk Extraction Using Response Surface Methodology

Coconut milk provides health benefits due to its medium chain fatty acids and is widely utilized in the food industry. However, there seems to be inadequate information on the optimal extraction conditions for coconut milk. In this study, a response surface methodology (RSM) based on central composite design (CCD) was employed to optimize the extraction time (X1), extraction temperature (X2) and particle size of coconut meat (X3) for coconut milk extraction. Yield, pH, viscosity and total solid content of coconut milk were evaluated as responses. Regression models were generated and adequacy tested with lack of fit test and coefficient of determination (R2). The results showed that extraction time; extraction temperature and particle size of coconut meat had significant (p˂ 0.05) effects on responses. The R2 for yield, pH, viscosity, and total solid content of coconut milk were 0.9976, 0.7352, 0.6748 and 0.9787 respectively. Optimum extraction time, temperature and particle size of coconut meat with the highest desirability index of 0.797 was 15 min, 40°C and ≤ 1617 µm respectively, while optimum yield, pH, viscosity, and total solid content of coconut milk were estimated at 61.129%, 6.6, 2.85 cp and 16.01% respectively. The experimental results obtained validate the predicted model within the acceptable range of the responses. The results also suggest that the obtained model is acceptable for the maximum milk yield and improved quality consistency.